Forecast dominance testing via sign randomization

• Verfasst von: Ehm, Werner [VerfasserIn]
• Verfasst von: Krüger, Fabian [VerfasserIn]
• Titel: Forecast dominance testing via sign randomization
• Verf.angabe: Werner Ehm and Fabian Krüger
• Jahr: 2018
• Umfang: 36 S.
• Fussnoten: Gesehen am 12.07.2019
• Titel Quelle: Enthalten in: Electronic journal of statistics
• Ort Quelle: Ithaca, NY : Cornell University Library, 2007
• Jahr Quelle: 2018
• Band/Heft Quelle: 12(2018), 2, Seite 3758-3793
• ISSN Quelle: 1935-7524
• DOI: doi:10.1214/18-EJS1495
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: Comparative forecast evaluation
• Sach-SW: hypothesis testing
• Sach-SW: randomization
• K10plus-PPN: 1669087778

Abstract

We propose randomization tests of whether forecast 1 outperforms forecast 2 across a class of scoring functions. This hypothesis is of applied interest: While the prediction context often prescribes a certain class of scoring functions, it is typically hard to motivate a specific choice on statistical or substantive grounds. We investigate the asymptotic behavior of the test statistics under mild conditions, avoiding the need to assume particular dynamic properties of forecasts and realizations. The properties of the one-sided tests depend on a corresponding version of Anderson’s inequality, which we state as a conjecture of independent interest. Numerical experiments and a data example indicate that the tests have good size and power properties in practically relevant situations.